Imaging light in motion and its application to tracking hidden objects

It is well known that light, the fastest entity in the universe, moves at a staggering speed of 300 millions meters per second. The ability to stop its flight on a centimetre scale or lower requires a detector with temporal resolution of around a hundred picoseconds. Freezing light in motion at this scale is a feat worth achieving, as it leads to a variety of exciting applications, from observing dynamical light phenomena to measuring distances and depths with high precision, as in LIDAR technology. In the past decades, different technologies have been developed to image light in motion; in this thesis, we propose a new method that exploit a recently-developed single-photon detector technology to capture movies of light in motion at very low intensity levels. We use this method to develop novel imaging applications and detection techniques. In particular, this thesis reports on the observation and study of dynamical light phenomena such as laser propagation in air, laser-induced plasma, propagation in optical fibres and slow light. We also show how the ability to record light in motion can be used to capture light signals scattered from around an obstacle, leading to the ability to locate and track moving objects hidden from view

Non-line-of-sight tracking of people at long range

A remote-sensing system that can determine the position of hidden objects has applications in many critical real-life scenarios, such as search and rescue missions and safe autonomous driving. Previous work has shown the ability to range and image objects hidden from the direct line of sight, employing advanced optical imaging technologies aimed at small objects at short range. In this work we demonstrate a long-range tracking system based on single laser illumination and single-pixel single-photon detection. This enables us to track one or more people hidden from view at a stand-off distance of over 50~m. These results pave the way towards next generation LiDAR systems that will reconstruct not only the direct-view scene but also the main elements hidden behind walls or corners

Detection and tracking of moving objects hidden from view

The ability to detect motion and track a moving object hidden around a corner or behind a wall provides a crucial advantage when physically going around the obstacle is impossible or dangerous. Previous methods have demonstrated that it is possible to reconstruct the shape of an object hidden from view. However, these methods do not enable the tracking of movement in real time. We demonstrate a compact non-line-of-sight laser ranging technology that relies on the ability to send light around an obstacle using a scattering floor and then detect the return signal from a hidden object within only a few seconds of acquisition time. By detecting this signal with a single-photon avalanche diode (SPAD) camera, we follow the movement of an object located a metre away from the camera with centimetre precision. We discuss the possibility of applying this technology to a variety of real-life situations in the near future

Picosecond time-resolved imaging using SPAD cameras

The recent development of 2D arrays of single-photon avalanche diodes (SPAD) has driven the development of applications based on the ability to capture light in motion. Such arrays are composed typically of 32x32 SPAD detectors, each having the ability to detect single photons and measure their time of arrival with a resolution of about 100 ps. Thanks to the single-photon sensitivity and the high temporal resolution of these detectors, it is now possible to image light as it is travelling on a centimetre scale. This opens the door for the direct observation and study of dynamics evolving over picoseconds and nanoseconds timescales such as laser propagation in air, laser-induced plasma and laser propagation in optical fibres. Another interesting application enabled by the ability to image light in motion is the detection of objects hidden from view, based on the recording of scattered waves originating from objects hidden by an obstacle. Similarly to LIDAR systems, the temporal information acquired at every pixel of a SPAD array, combined with the spatial information it provides, allows to pinpoint the position of an object located outside the line-of-sight of the detector. A non-line-of-sight tracking can be a valuable asset in many scenarios, including for search and rescue mission and safer autonomous driving

How Are Adolescents Sleeping? Adolescent Sleep Patterns and Sociodemographic Differences in 24 European and North American Countries

© 2020 Published by Elsevier Inc. on behalf of Society for Adolescent Health and Medicine. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Purpose: Insufficient and poor sleep patterns are common among adolescents worldwide. Up to now, the evidence on adolescent sleep has been mostly informed by country-specific studies that used different measures and age groups, making direct comparisons difficult. Cross-national data on adolescent sleep that could inform nations and international discussions are lacking. We examined the sleep patterns of adolescents across 24 countries and by gender, age, and affluence groups. Methods: We obtained sleep data on 165,793 adolescents (mean age 13.5 years; 50.5% girls) in 24 European and North American countries from the recent cross-sectional Health Behaviour in School-aged Children surveys (2013–2014 and 2017–2018). For each country, we calculated the age-standardized mean in sleep duration, timing, and consistency and the proportions meeting sleep recommendations on school and nonschool days from self-reported bedtimes and wake times. We conducted stratified analyses by gender, age, and family affluence group. Results: Adolescent sleep patterns varied cross-nationally. The average sleep duration ranged between 7:47 and 9:07 hours on school days and between 9:31 and 10:22 hours on nonschool days, and the proportion of adolescents meeting sleep recommendations ranged between 32% and 86% on school days and between 79% and 92% on nonschool days. Sleep patterns by gender and affluence groups were largely similar, but older adolescents slept less and went to bed later on school days than younger adolescents in all countries. Conclusions: The sleep patterns of adolescents vary across countries and sociodemographic groups. Insufficient sleep on school days is common in many countries. Public health and policy efforts to promote healthy adolescent sleep are encouraged.The work was supported by the European Regional Development Fund-Project "Effective Use of Social Research Studies for Practice" (No. CZ.02.1.01/0.0/0.0/16_025/0007294) and by funding from the Technology Agency of the Czech Republic (ÉTA TL01000335) and the Ministry of Education, Youth and Sports, Inter-Excellence, LTT18020 (HBSC Czech Republic); the Public Health Agency of Canada (HBSC Canada); the Juho Vainio Foundation and the University of Jyvaskyla (HBSC Finland); and the Portugal- National Foundation for Science and Technology (HBSC Portugal).info:eu-repo/semantics/publishedVersio

Neighbourhood characteristics and depression in community-dwellers with and without a chronic condition

Background: Depression is a serious public-health problem and the leading cause of disability worldwide. Studies have shown neighbourhood characteristics to be associated with depression, but it is not clear which neighbourhood features matter most for depression, for whom this effect is most relevant and what pathways explain this association. Individuals with a chronic disease, such as diabetes, rely on their local area for resources and support, and might be particularly vulnerable in this context. Objectives: To assess the association of neighbourhood characteristics on risk of depression in adults with and without a chronic condition (objective 1); to examine potential moderators and mediators of this association (objective 2); and to explore the relationship between neighbourhood characteristics and changes in depression over time (objective 3).Design and methods: Secondary data analyses were conducted using two cohort studies combined with census, geospatial, satellite imagery and survey data. In a first step, I adopted a wide perspective to examine neighbourhood effects in the general population with and without a chronic condition, using 10 years of data from the National Population Health Survey (NPHS; 2000/01-2010/11; n=17,276 at baseline). In a second step, I focused specifically on people with type 2 diabetes, using 5 years of data from the Diabetes Health Study (DHS; 2008-2013; n=2003 at baseline). The two surveys were analyzed separately. Depression was measured using screening tools. For objective 1, I conducted survival analyses to examine the associations of neighbourhood factors and incident depression, in those with and without a chronic condition. For objective 2, I included interaction terms in the models and stratified analyses to investigate potential moderators. I performed a novel mediation analysis using the additive hazard model to examine potential mediators. For objective 3, I used latent class growth modelling to examine the associations of time-varying neighbourhood factors on trajectories of depression over time.Project 1 - Neighbourhoods and risk of depression in people with and without a chronic condition (NPHS data). Neighbourhood characteristics were not significantly associated with risk of depression in the general sample and in subsamples with a chronic condition. However, moderator analysis revealed that living in proximity to a park was associated with lower risk of depression for people living in crowded households.Project 2 - Neighbourhoods and risk of depression in people with diabetes (DHS data). A greater number of physical activity facilities, cultural services and level of greenness in the neighbourhood were associated with lower risk of depression. Material deprivation was associated with increased risk of depression, particularly in adults with diabetes who were older or retired. Reduction in diabetes complications and disability were significant mediators in the pathway between neighbourhood fitness facilities and depression.Project 3 - Neighbourhoods and trajectories of depression over time (NPHS data). Latent class growth modelling uncovered three distinct trajectories of major depression prevalence: low; moderate decreasing; and high persistent. The presence of neighbourhood parks and cultural services was associated with a significant shift in the trajectory of high persistent depression towards lower probability of major depression. Conclusions: Aspects of the neighbourhood environment were significantly related to risk of depression, particularly in vulnerable subgroups, such as those with diabetes, those living in crowded households and those with persistent major depression symptoms. Future intervention research is needed for health policy recommendations.Contexte: La dépression est un problème de santé publique majeur. Des études montrent des associations entre certaines caractéristiques du voisinage et la dépression. Par contre, nous ne savons toujours pas quels aspects du voisinage ont le plus grand impact sur la dépression, quelles personnes sont les plus affectées et par quel mécanisme existe cette association. Les personnes ayant une maladie chronique dépendent du soutien et des ressources de leur voisinage, et donc pourraient être particulièrement vulnérables par leurs contextes environnementaux. Objectifs: Évaluer l'association entre les caractéristiques du voisinage et le risque de dépression chez des adultes avec et sans maladie chronique (objectif 1); examiner les modérateurs et les médiateurs qui contribuent à cette association (objectif 2); et étudier la relation entre les caractéristiques de voisinage et les changements de la dépression à travers le temps (objectif 3). Conception et méthodes: Cette thèse est une l'analyse de données secondaires tirées de deux enquêtes canadiennes, combinées avec des données provenant de recensements, de bases de données géospatiales, d'imagerie satellite, et de sondages. En premier lieu, j'ai adopté une perspective globale des effets de voisinage dans la population générale en me servant de 10 ans de données de l'Enquête nationale sur la santé de la population (ENSP 2000/01-2010/11, n = 17,276 au départ). En deuxièmement lieu, je me suis portée plus spécifiquement sur les personnes atteintes de diabète de type 2, en me servant de 5 ans de données de l'Étude sur la santé du diabète (ESD; 2008-2013; n = 2003 au départ). Les analyses des deux enquêtes ont été faites séparément. La dépression a été mesurée à l'aide d'outils de dépistage. Pour l'objectif 1, j'ai effectué des analyses de survie pour examiner les associations entre les caractéristiques du voisinage et le risque de dépression chez les gens avec et sans maladie chronique. Pour l'objectif 2, j'ai testé des modérateurs en incluant des termes d'interaction dans les modèles et j'ai testé des potentiels à l'aide du modèle de risques additifs. Pour l'objectif 3, j'ai utilisé une analyse de croissance de classe latente afin d'examiner l'effet des caractéristiques des voisinages sur les trajectoires de la dépression. Projet 1 - Voisinages et le risque de dépression chez les personnes avec et sans maladie chronique (des données de l'ENSP). Les caractéristiques des voisinages n'étaient pas associées de façon significative à un risque de dépression dans l'échantillon général, ni dans les sous-échantillons de personnes ayant une maladie chronique. Cependant, l'analyse des modérateurs a révélé qu'habiter près d'un parc était associé à un risque de dépression moindre pour les personnes vivant dans des logements surpeuplés. Projet 2 - Voisinages et le risque de dépression chez les personnes atteintes de diabète (données de l'ESD). Un plus grand nombre d'installations d'activité physique, de services culturels, et un taux plus élevé de verdure dans le voisinage étaient associés à un risque moindre de dépression. La privation matérielle était associée à un risque accru de dépression, en particulier chez les personnes avec le diabète qui étaient plus âgés ou à la retraite. La réduction des complications du diabète et de l'invalidité était des médiateurs importants expliquant le lien entre les installations d'activité physique et la dépression chez les personnes diabétiques. Projet 3 - Voisinages et trajectoires de dépression au cours du temps (données de l'ENSP). La modélisation de croissance de classe latente a révélé trois trajectoires de prévalence de dépression majeure: faible prévalence, prévalence modéré diminuant avec le temps, et prévalence élevée chronique. La présence de parcs et de services culturels dans le voisinage était associée de façon significative à un changement dans la trajectoire de dépression élevée chronique vers une probabilité moindre de dépression majeure

PLOS2017adolescents_dataset.dta

This data set uses data publicly available data from the Panel Survey of Income Dynamics (http://psidonline.isr.umich.edu/) to study the effect of early-life exposure to low family income and adolescent subjective well-bein